Los Alamos National Laboratory
Phone| Search
T-5 HomeResearchPublications › weronski-2007-bacterial
› Contact › People › Research
› Projects › Highlights › Publications
› Jobs › Visitor Info

Cite Details

Alexis J. de Kerchove, Pawel Weronski and Menachem Elimelech, "Deposition of Bacteria (Pseudomonas Aeruginosa) on "Soft" Polyelectrolyte Layer: Measurements and Model Predictions", Langmuir, vol. 23, pp. 12301-8, 2007


Prediction of bacterial deposition rates onto substrates in natural aquatic systems is quite challenging because of the inherent complexity of such systems. In this study, we compare experimental deposition kinetics of nonmotile bacteria (Pseudomonas aeruginosa) on an alginate-coated substrate in a radial stagnation point flow (RSPF) system to predictions based on DLVO theory. The "softness" of the surface layer of the bacteria and alginate-coated substrate was considered in the calculations of their electrokinetic surface properties, and the relevance of both the classical zeta potential and the outer surface potential as surrogates for surface potential was investigated. Independent of the used electrical potentials, we showed that significant discrepancies exist between theory and experiments. Analysis of microscopic images in the RSPF system has demonstrated, for the first time, that irreversible deposition of particles or cells entrapped in the secondary energy minimum can occur on the alginate layer, despite the hydrodynamic forces resulting from the radial flow in the RSPF system. It is suggested that polymeric structures associated with the surface of the particle/cell and the alginate-coated substrate are responsible for the transition between the secondary minimum and primary energy well. This mode of deposition is likely to be important in the deposition of microorganisms in complex aquatic systems.

BibTeX Entry

author = {Alexis J. de Kerchove and Pawel Weronski and Menachem Elimelech},
title = {Deposition of Bacteria (Pseudomonas Aeruginosa) on "Soft" Polyelectrolyte Layer: Measurements and Model Predictions},
year = {2007},
urlpdf = {http://dx.doi.org/10.1021/la701936x},
journal = {Langmuir},
volume = {23},
pages = {12301-8}